arXiv:2512.11186cs.CV2025-12中稿 · DCC2026 Oral被引 4

用视频编码器压缩3D高斯点云,速度提升50%且码率更低。

Lightweight 3D Gaussian Splatting Compression via Video Codec

  • 两阶段莫顿扫描生成适合编码器的分块2D图
  • 低码率下性能超越现有方法20%以上
  • 适合移动端和轻量设备实时应用

现有基于视频的3D高斯点云(GS)压缩方法依赖并行线性分配排序(PLAS),计算开销大、耗时长,限制了在轻量设备上的应用。本文提出基于视频编码器的轻量级3D高斯点云压缩方法(LGSCV)。首先采用两阶段莫顿扫描:先用3D莫顿扫描排列高斯原语,再用2D莫顿扫描将其映射为分块式2D图,适配标准视频编码器的方形编码单元(CU)。尽管该方法在高码率下性能接近PLAS,但在中低码率下质量下降明显。为此,引入球谐函数(SH)的主成分分析(PCA)降维,并设计快速灵活的MiniPLAS,在局部块内重新排列原语。结合SH PCA与MiniPLAS后,码率-失真(RD)性能显著提升,尤其在中低码率下表现突出。此外,MiniPLAS可指导编码器CU大小设置,大幅降低编码时间。在MPEG数据集上的实验表明,LGSCV相比当前最优方法实现超20%的RD增益,2D图生成时间降至约1秒,编码时间减少50%。代码已开源。

原文摘要 · Abstract (English)

Current video-based GS compression methods rely on using Parallel Linear Assignment Sorting (PLAS) to convert 3D GS into smooth 2D maps, which are computationally expensive and time-consuming, limiting the application of GS on lightweight devices. In this paper, we propose a Lightweight 3D Gaussian Splatting (GS) Compression method based on Video codec (LGSCV). First, a two-stage Morton scan is proposed to generate blockwise 2D maps that are friendly for canonical video codecs in which the coding units (CU) are square blocks. A 3D Morton scan is used to permute GS primitives, followed by a 2D Morton scan to map the ordered GS primitives to 2D maps in a blockwise style. However, although the blockwise 2D maps report close performance to the PLAS map in high-bitrate regions, they show a quality collapse at medium-to-low bitrates. Therefore, a principal component analysis (PCA) is used to reduce the dimensionality of spherical harmonics (SH), and a MiniPLAS, which is flexible and fast, is designed to permute the primitives within certain block sizes. Incorporating SH PCA and MiniPLAS leads to a significant gain in rate-distortion (RD) performance, especially at medium and low bitrates. MiniPLAS can also guide the setting of the codec CU size configuration and significantly reduce encoding time. Experimental results on the MPEG dataset demonstrate that the proposed LGSCV achieves over 20% RD gain compared with state-of-the-art methods, while reducing 2D map generation time to approximately 1 second and cutting encoding time by 50%. The code is available at https://github.com/Qi-Yangsjtu/LGSCV .

3D重建视频编码轻量化

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